Department of Chemistry, University of Kansas, 2030 Becker Drive, Lawrence, KS, 66047, USA.
Anal Bioanal Chem. 2017 Jan;409(2):561-570. doi: 10.1007/s00216-016-9896-y. Epub 2016 Sep 10.
Protein glycosylation drives many biological processes and serves as markers for disease; therefore, the development of tools to study glycosylation is an essential and growing area of research. Mass spectrometry can be used to identify both the glycans of interest and the glycosylation sites to which those glycans are attached, when proteins are proteolytically digested and their glycopeptides are analyzed by a combination of high-resolution mass spectrometry (MS) and tandem mass spectrometry (MS/MS) methods. One major challenge in these experiments is collecting the requisite MS/MS data. The digested glycopeptides are often present in complex mixtures and in low abundance, and the most commonly used approach to collect MS/MS data on these species is data-dependent acquisition (DDA), where only the most intense precursor ions trigger MS/MS. DDA results in limited glycopeptide coverage. Semi-targeted data acquisition is an alternative experimental approach that can alleviate this difficulty. However, due to the massive heterogeneity of glycopeptides, it is not obvious how to expediently generate inclusion lists for these types of analyses. To solve this problem, we developed the software tool GlycoPep MassList, which can be used to generate inclusion lists for liquid chromatography tandem-mass spectrometry (LC-MS/MS) experiments. The utility of the software was tested by conducting comparisons between semi-targeted and untargeted data-dependent analysis experiments on a variety of proteins, including IgG, a protein whose glycosylation must be characterized during its production as a biotherapeutic. When the GlycoPep MassList software was used to generate inclusion lists for LC-MS/MS experiments, more unique glycopeptides were selected for fragmentation. Generally, ∼30 % more unique glycopeptides can be analyzed per protein, in the simplest cases, with low background. In cases where background ions from proteins or other interferents are high, usage of an inclusion list is even more advantageous. The software is freely publically accessible. Graphical abstract Software increases the number of glycopeptides that get selected for MS/MS analysis.
蛋白质糖基化驱动许多生物过程，并作为疾病的标志物；因此，开发研究糖基化的工具是一个必不可少且不断发展的研究领域。当蛋白质经蛋白酶解后，其糖肽通过高分辨质谱（MS）和串联质谱（MS/MS）方法的组合进行分析时，质谱可用于鉴定感兴趣的聚糖和糖基化位点。在这些实验中，一个主要的挑战是收集必要的 MS/MS 数据。消化的糖肽通常存在于复杂的混合物中，并且丰度较低，最常用的方法是数据依赖型采集（DDA），其中只有最强烈的前体离子触发 MS/MS。DDA 导致糖肽覆盖率有限。半靶向数据采集是一种替代的实验方法，可以缓解这一困难。然而，由于糖肽的巨大异质性，如何方便地为这些类型的分析生成包含列表并不明显。为了解决这个问题，我们开发了软件工具 GlycoPep MassList，它可以用于为液相色谱串联质谱（LC-MS/MS）实验生成包含列表。通过在各种蛋白质（包括 IgG）上进行半靶向和非靶向数据依赖型分析实验的比较，测试了该软件的实用性，其中 IgG 是在作为生物治疗剂生产过程中必须进行糖基化特征分析的一种蛋白质。当使用 GlycoPep MassList 软件为 LC-MS/MS 实验生成包含列表时，更多独特的糖肽被选择用于片段化。一般来说，在最简单的情况下，每个蛋白质可以分析多达 30%的独特糖肽，背景低。在蛋白质或其他干扰物的背景离子较高的情况下，使用包含列表甚至更有利。该软件免费公开提供。
